Implementing social media into nursing education
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Social media is an aspect of everyday life for many undergraduate nursing students and can also be beneficial from an education perspective. Popular social media platforms can be used as often as daily for many nursing students. The emergence of Generation Z (born between 2995-2010) as the predominant population of nursing students calls for a shift in pedagogical approaches; one that accommodates the needs of the unique demographic. This narrative literature review examines how social media can provide an effective pedagogical tool to engage the modern undergraduate nursing student by providing a platform for accessible educational activities, fostering professional identity and encourages virtual professionalism for this unique Generation. Guided by a constructivist approach and the Social Media for Learning (SM4L) framework, this pedagogical approach could foster student engagement and promote appropriate use of social media in the personal and professional lives of nursing students. Additionally, these innovative nurses can enter the workforce prepared to use social media tools to disseminate health information and patient teaching appropriately and professionally, providing better access and improved care for patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it